Systems and methods for multi-user multi-lingual communications
View Patent ↗Various embodiments described herein facilitate multi-lingual communications. The systems and methods of some embodiments enable multi-lingual communications through different modes of communication including, for example, Internet-based chat, e-mail, text-based mobile phone communications, postings to online forums, postings to online social media services, and the like. Certain embodiments implement communication systems and methods that translate text between two or more languages. Users of the systems and methods may be incentivized to submit corrections for inaccurate or erroneous translations, and may receive a reward for these submissions. Systems and methods for assessing the accuracy of translations are described.
1. A method implemented by at least one computer processor, the method comprising:
obtaining, from a client device of a user, a text message in a first language, the text message comprising at least one word;
providing, using the at least one computer processor, the text message to a machine translation system;
obtaining, using the at least one computer processor, a translation of the text message from the machine translation system;
determining, using the at least one computer processor, that the text message and the translation both comprise the at least one word in the first language and that the at least one word is correctly spelled; and
performing one or more of the following:
(a) determining, using the at least one computer processor, Bayesian probabilities for neighboring words that appear before and after the at least one word and, when the Bayesian probabilities exceed a threshold value, adding the at least one word to a lexicon in a data store; and
(b) performing, using the at least one computer processor, k-means clustering to identify a cluster of words comprising synonyms and, when the cluster comprises the at least one word, adding the at least one word to the lexicon in the data store.
2. The method of claim 1 , wherein the at least one word comprises an out of vocabulary word.
3. The method of claim 1 , wherein the at least one word comprises a new chatspeak word.
4. The method of claim 1 , further comprising determining whether the lexicon in the data store comprises the at least one word.
5. The method of claim 1 , wherein the user is a player in an online game.
6. The method of claim 1 , wherein the lexicon comprises words in a vocabulary of the first language.
7. The method of claim 1 , wherein determining Bayesian probabilities comprises (i) reviewing previous uses of the at least one word in prior text messages and (ii) identifying words, if any, that appear before and after the at least one word in the prior text messages.
8. The method of claim 1 , wherein the Bayesian probabilities provide an indication of a likelihood that the neighboring words will appear before and after the at least one word in the text message.
9. The method of claim 1 , wherein identifying the cluster comprises reviewing prior text messages and identifying words used in a similar context as the at least one word in the text message.
10. The method of claim 1 , further comprising analyzing the syntax and semantics of the text message to determine parts of speech present in the text message.
11. A system comprising:
a non-transitory computer readable medium having instructions stored thereon; and
a data processing apparatus configured to execute the instructions to perform operations comprising:
obtaining, from a client device of a user, a text message in a first language, the text message comprising at least one word;
providing the text message to a machine translation system;
obtaining a translation of the text message from the machine translation system;
determining that the text message and the translation both comprise the at least one word in the first language and that the at least one word is correctly spelled; and
performing one or more of the following:
(a) determining Bayesian probabilities for neighboring words that appear before and after the at least one word and, when the Bayesian probabilities exceed a threshold value, adding the at least one word to a lexicon in a data store; and
(b) performing k-means clustering to identify a cluster of words comprising synonyms and, when the cluster comprises the at least one word, adding the at least one word to the lexicon in the data store.
12. The system of claim 11 , wherein the at least one word comprises an out of vocabulary word.
13. The system of claim 11 , wherein the at least one word comprises a new chatspeak word.
14. The system of claim 11 , the operations further comprising determining whether the lexicon in the data store comprises the at least one word.
15. The system of claim 11 , wherein the user is a player in an online game.
16. The system of claim 11 , wherein the lexicon comprises words in a vocabulary of the first language.
17. The system of claim 11 , wherein determining Bayesian probabilities comprises (i) reviewing previous uses of the at least one word in prior text messages and (ii) identifying words, if any, that appear before and after the at least one word in the prior text messages.
18. The system of claim 11 , wherein the Bayesian probabilities provide an indication of a likelihood that the neighboring words will appear before and after the at least one word in the text message.
19. The system of claim 11 , wherein identifying the cluster comprises reviewing prior text messages and identifying words used in a similar context as the at least one word in the text message.
20. The system of claim 11 , the operations further comprising analyzing the syntax and semantics of the text message to determine parts of speech present in the text message.
21. A computer program product stored in one or more non-transitory storage media for controlling a processing mode of a data processing apparatus, the computer program product being executable by the data processing apparatus to cause the data processing apparatus to perform operations comprising:
obtaining, from a client device of a user, a text message in a first language, the text message comprising at least one word;
providing the text message to a machine translation system;
obtaining a translation of the text message from the machine translation system;
determining that the text message and the translation both comprise the at least one word in the first language and that the at least one word is correctly spelled; and
performing one or more of the following:
(a) determining Bayesian probabilities for neighboring words that appear before and after the at least one word and, when the Bayesian probabilities exceed a threshold value, adding the at least one word to a lexicon in a data store; and
(b) performing k-means clustering to identify a cluster of words comprising synonyms and, when the cluster comprises the at least one word, adding the at least one word to the lexicon in the data store.
22. The computer program product of claim 21 , wherein the at least one word comprises an out of vocabulary word.
23. The computer program product of claim 21 , wherein the at least one word comprises a new chatspeak word.
24. The computer program product of claim 21 , the operations further comprising determining whether the lexicon in the data store comprises the at least one word.
25. The computer program product of claim 21 , wherein the user is a player in an online game.
26. The computer program product of claim 21 , wherein the lexicon comprises words in a vocabulary of the first language.
27. The computer program product of claim 21 , wherein determining Bayesian probabilities comprises (i) reviewing previous uses of the at least one word in prior text messages and (ii) identifying words, if any, that appear before and after the at least one word in the prior text messages.
28. The computer program product of claim 21 , wherein the Bayesian probabilities provide an indication of a likelihood that the neighboring words will appear before and after the at least one word in the text message.
29. The computer program product of claim 21 , wherein identifying the cluster comprises reviewing prior text messages and identifying words used in a similar context as the at least one word in the text message.
30. The computer program product of claim 21 , the operations further comprising analyzing the syntax and semantics of the text message to determine parts of speech present in the text message.